45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026Department of Computer Science, Salesforce AI ResearchSalesforce ResearchU Wisconsin, MadisonMulti-agent LLM systemsSkillOrchestra: Learning to Route Agents via Skill TransferJiayu Wang, Yifei Ming, Zixuan Ke, Shafiq Joty and 2 moreSydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet0/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 0 of 20 reviewers recommend itlenient 0/5medium 0/10strict 0/5
57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026Department of Computer Science, Time series classification & imputationMissPath-FM: Flow Matching with Structured Priors for Partially Observed Time SeriesGenpei ZhangSydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet1/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 1 of 20 reviewers recommend itlenient 1/5medium 0/10strict 0/5
57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026U Wisconsin - MadisonDepartment of Computer Science, UW-MadisonDeep RLAnatomy of Off-Policy Policy Gradient: Importance Sampling, KL Regularization, and BaselinesHaoqun Cao, Yurun Yuan, Tengyang XieSydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet1/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 1 of 20 reviewers recommend itlenient 1/5medium 0/10strict 0/5
88%Must read?Must readVote to see the scoreNeurIPS 2026Ai2PurdueU Wisconsin - MadisonDepartment of Computer Science, RutgersFlow matchingLearning Visual Feature-Based World Models via Residual Latent ActionResidual Latent Action predicts visual feature dynamics via flow matching, outperforming diffusion world models with orders-of-magnitude faster inference and enabling offline robot learning from videos.Xinyu Zhang, Zhengtong Xu, Yutian Tao, Yeping Wang and 2 moreAtlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 3 on Hugging Face · Code ★ 47– ReadersNo votes yet15/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 15 of 20 reviewers recommend itlenient 5/5medium 9/10strict 1/5